A spatio-temporal fusion method for remote sensing data Using a linear injection model and local neighbourhood information

This paper presents a spatio-temporal fusion method for remote sensing images by using a linear injection model and local neighbourhood information. In this method, the linear injection model is first introduced to generate an initial fused image, the spatial details are extracted from the fine-resolution image at the base date, and are weighted by a proper injection gains. Then, the spatial details and the relative spectral information from the coarse-resolution images are blended to generate the fusion result. To further enhance its robustness to the noise, the local neighbourhood information, derived from the fine-resolution image and the fused result simultaneously, is introduced to refine the initial fused image to obtain a more accurate prediction result. The algorithm can effectively capture phenology change or land-cover-type change with minimum input data. Simulated data and two types of real satellite images with seasonal changes and land-cover-type changes are employed to test the performance of the proposed method. Compared with a spatial and temporal adaptive reflectance fusion model (STARFM) and a flexible spatio-temporal fusion algorithm (FSDAF), results show that the proposed approach improves the accuracy of fused images in phenology change area and effectively captures land-cover-type reflectance changes.     

Specific emitter identification for satellite communication using probabilistic neural networks

Electromagnetic signal emitted by satellite communication (satcom) transmitters are used to identify specific individual uplink satcom terminals sharing the common transponder in real environment, which is known as specific emitter identification (SEI) that allows for early indications and warning (I&W) of the targets carrying satcom furnishment and furthermore the real time electromagnetic situation awareness in military operations. In this paper, the authors are the first to propose the identification of specific transmitters of satcom by using probabilistic neural networks (PNN) to reach the goal of target recognition. We have been devoted to the examination by exploring the feasibility of utilizing the Hilbert transform to signal preprocessing, applying the discrete wavelet transform to feature extraction, and employing the PNN to perform the classification of stationary signals. There are a total of 1000 sampling time series with binary phase shift keying (BPSK) modulation originated by five types of satcom transmitters in the test. The established PNNs classifier implements the data testing and finally yields satisfactory accuracy at 8 dB(±1 dB) carrier to noise ratio, which indicates the feasibility of our method, and even the keen insight of its application in military.     

Influence of geosynthetic reinforcement on the stability of an embankment with rigid columns embedded in an inclined underlying stratum

Incompressible dipping substrata are commonly encountered in engineering practice. Compared to horizontal underlying strata, the inclined underlying stratum increase the risk of collapse of embankments reinforced with columns because it weakens the restraint of the column base. The objective of this study is to investigate the effectiveness of geosynthetics on improving the embankment stability when the underlying stratum is inclined. The influence of geosynthetic tensile stiffness on the ultimate surcharge and failure mechanism is studied. A deep-seated failure with column tilting occurs when the geosynthetic tensile stiffness is low, whereas a lateral sliding occurs when the geosynthetic tensile stiffness is high. To illustrate the contribution of geosynthetics, the distribution of the lateral pressures acting on the columns is analyzed.     

Crystallographic characteristics and microwave dielectric properties of Ni-modified MgTa2O6 ceramics

Ni²⁺ modified MgTa₂O₆ ceramics with a trirutile phase and space group P4₂/mnm were obtained. The correlations between crystallographic characteristics and microwave dielectric performance of MgTa₂O₆ ceramics were systematically studied based on the chemistry bond theory (PVL theory) for the first time. The results indicate that the introduction of Ni²⁺ causes a change in polarizability and the Mg–O bond ionicity, which contributes to the variation of dielectric constant. Moreover, the lattice energy, and packing fraction, full width at half maximum of the Raman peak of Ta–O bond, as the quantitative characterization of crystallographic parameters, regulate the dielectric loss of MgTa₂O₆ ceramics in GHz frequency band. In addition, the study of sintering behavior shows that the densification and micromorphology are the crucial factors affecting the microwave dielectric performance. Typically, Ni²⁺ doping on the A-site of MgTa₂O₆ can effectively promote the Q × f values to 173,000 GHz (at 7.43 GHz), which ensures its applicability in 5G communication technology.     

Investigation of crystal characteristics,Raman spectra,and microwave dielectric properties of Mg1-xZnxTa2O6 ceramics

Mg_(1-x)Zn_xTa₂O₆ (x = 0.00?0.08) dielectric ceramics were synthesized via the traditional solid-state reaction method. We used XRD and Rietveld refinement to demonstrate that a pure Mg_(1-x)Zn_xTa₂O₆ phase with trirutile structure was formed. Zn²⁺ substitution helped to decrease the Raman full width at half width of the A_1g mode at 703 cm^?1, which resulted in an increase in the order and rigidity of the TaO₆ octahedron, this in turn contributed to improving the Q×f values. Additionally, the introduction of Zn²⁺ significantly promoted grain growth and increased the dense, and the molecular polarizability, these factors lead to a higher permittivity. Moreover, enhanced Ta-O bond energy resulted in a more stable TaO₆ octahedron in the Mg_(1?x)Zn_xTa₂O₆ system, which contributed to enhanced τ_f values via substitution of Zn²⁺ doped on the A-site. Correspondingly, the microwave dielectric properties were significantly improved for 0.04-doped samples, obtaining: ε_r = 27, Q × f = 185,000 GHz (at 7.47 GHz), τ_f =32 ppm/°C.     

Traffic identification method based on multiple probabilistic neural network model

Neural Computing and Applications - Traffic identification is currently an important challenge for network management and security. In this paper, we propose a novel application identification...     

Attitude dynamics of coupled spacecraft undergoing fuel transfer

Multibody System Dynamics - This paper represents an explicit analytical solution for attitude dynamics of spacecraft combination during on-orbit refueling. Due to the fuel transfer from the...     

Regulation of sensory nerve conduction velocity of human bodies responding to annual temperature variations in natural environments

The extensive research interests in environmental temperature can be linked to human productivity / performance as well as comfort and health; while the mechanisms of physiological indices responding to temperature variations remain incompletely understood. This study adopted a physiological sensory nerve conduction velocity (SCV) as a temperature‐sensitive biomarker to explore the thermoregulatory mechanisms of human responding to annual temperatures. The measurements of subjects’ SCV (over 600 samples) were conducted in a naturally ventilated environment over all four seasons. The results showed a positive correlation between SCV and annual temperatures and a Boltzmann model was adopted to depict the S‐shaped trend of SCV with operative temperatures from 5°C to 40°C. The SCV increased linearly with operative temperatures from 14.28°C to 20.5°C and responded sensitively for 10.19°C‐24.59°C, while tended to be stable beyond that. The subjects’ thermal sensations were linearly related to SCV, elaborating the relation between human physiological regulations and subjective thermal perception variations. The findings reveal the body SCV regulatory characteristics in different operative temperature intervals, thereby giving a deeper insight into human autonomic thermoregulation and benefiting for built environment designs, meantime minimizing the temperature‐invoked risks to human health and well‐being.